Innovative Research Award
Mehdi Yalaoui
University Of Science And Technology Houari Boumediene, Algeria
| Mehdi Yalaoui |
| Affiliation |
University Of Science And Technology Houari Boumediene |
| Country |
Algeria |
| Scopus ID |
57468299400 |
| Documents |
2 |
| Citations |
5 |
| h-index |
1 |
| Subject Area |
Data Quality |
| Event |
Global Tech Excellence Awards |
Mehdi Yalaoui is a researcher affiliated with the University Of Science And Technology Houari Boumediene in Algeria whose academic work focuses on data quality and the management of heterogeneous information sources. His research addresses data quality assessment, taxonomies, and structured approaches for improving external and social media data, contributing to reliable data-driven analysis and decision-making. [1] [2]
Abstract
Mehdi Yalaoui’s research is centered on data quality, with particular attention to the assessment and management of heterogeneous external and social media data. His work examines structured methods for understanding data entities, quality dimensions, relationships, and assessment processes. His publications address both conceptual foundations and practical approaches to improving data reliability for analytics and decision-making. The research contributes to ongoing discussions surrounding data governance and quality management in increasingly complex information environments. [1] [2]
Keywords
- Data Quality
- Data Quality Management
- External Data
- Social Media Data
- Data Assessment
- Data Governance
- Big Data
Introduction
Data quality has become an important research concern as organizations increasingly depend on large, heterogeneous, and rapidly generated information sources. Yalaoui and Boukhedouma examine data quality principles, taxonomies, assessment approaches, and improvement processes, emphasizing the need for systematic methods capable of addressing complexity associated with contemporary data environments and supporting dependable organizational decision-making. [2]
Research Profile
Yalaoui’s research profile is concentrated in data quality and related information-management challenges. His documented publications address conceptual frameworks for data-quality assessment and a metamodel designed for external and social media data. This profile demonstrates an academic interest in organizing complex data environments through structured concepts, quality dimensions, relationships, and systematic assessment mechanisms. [1] [2]
Research Contributions
A principal contribution of Yalaoui’s research is the development of a comprehensive metamodel for external and social media data quality management. The work organizes data categories, quality dimensions, and relationships into a structured framework, while also considering assessment and improvement requirements. This approach provides a conceptual basis for addressing heterogeneous data-quality challenges. [1]
Publications
Yalaoui’s documented publication record includes research on data-quality principles, taxonomies, assessment approaches, and a metamodel for external and social media data. The publications demonstrate continuity in the researcher’s subject focus and address both theoretical classification and practical quality-management considerations. Together, these works establish a coherent scholarly direction centered on improving the reliability of complex data. [1] [2]
Research Impact
The potential impact of Yalaoui’s work lies in supporting more systematic approaches to data-quality management across heterogeneous information sources. By addressing external and social media data, his research considers environments where inconsistency, variability, and complex relationships can affect analytical reliability. Such frameworks may assist researchers and practitioners in evaluating data quality and improving downstream decision-making processes. [1] [2]
Award Suitability
Yalaoui demonstrates relevance to the Innovative Research Award through focused scholarly work addressing contemporary data-quality challenges. His research combines conceptual analysis with a structured metamodel for external and social media data, reflecting an effort to extend established quality-management approaches to evolving information environments. The documented publication trajectory supports consideration for recognition in data-quality research. [1] [2]
Conclusion
Mehdi Yalaoui’s research presents a consistent focus on data quality and its management within increasingly heterogeneous information environments. His work addresses foundational principles while proposing structured approaches for external and social media data. These contributions provide a relevant academic basis for continued research into data assessment, quality improvement, and dependable data-driven decision-making. [1] [2]
External Links
References
- Yalaoui, M., & Boukhedouma, S. (2025). Enhancing Data Quality Management: A Comprehensive Metamodel for External and Social Media Data. IEEE.
https://ieeexplore.ieee.org/document/11081960
- Yalaoui, M., & Boukhedouma, S. (2021). A survey on data quality: Principles, taxonomies and comparison of approaches. In 2021 International Conference on Information Systems and Advanced Technologies (ICISAT) (pp. 1–9). IEEE.
https://doi.org/10.1109/ICISAT54145.2021.9678209
- Elsevier. (n.d.). Scopus author details: Mehdi Yalaoui, Author ID 57468299400. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57468299400